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Advanced Elasticsearch 7.0

You're reading from   Advanced Elasticsearch 7.0 A practical guide to designing, indexing, and querying advanced distributed search engines

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Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781789957754
Length 560 pages
Edition 1st Edition
Languages
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Author (1):
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Wai Tak Wong Wai Tak Wong
Author Profile Icon Wai Tak Wong
Wai Tak Wong
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Table of Contents (25) Chapters Close

Preface 1. Section 1: Fundamentals and Core APIs FREE CHAPTER
2. Overview of Elasticsearch 7 3. Index APIs 4. Document APIs 5. Mapping APIs 6. Anatomy of an Analyzer 7. Search APIs 8. Section 2: Data Modeling, Aggregations Framework, Pipeline, and Data Analytics
9. Modeling Your Data in the Real World 10. Aggregation Frameworks 11. Preprocessing Documents in Ingest Pipelines 12. Using Elasticsearch for Exploratory Data Analysis 13. Section 3: Programming with the Elasticsearch Client
14. Elasticsearch from Java Programming 15. Elasticsearch from Python Programming 16. Section 4: Elastic Stack
17. Using Kibana, Logstash, and Beats 18. Working with Elasticsearch SQL 19. Working with Elasticsearch Analysis Plugins 20. Section 5: Advanced Features
21. Machine Learning with Elasticsearch 22. Spark and Elasticsearch for Real-Time Analytics 23. Building Analytics RESTful Services 24. Other Books You May Enjoy

Mapping APIs

In the last chapter, we learned about the document life cycle of Elasticsearch and executed single and multiple document APIs. We introduced a commission-free ETF from TD Ameritrade and used this information to practice document APIs. We also reindexed the documents from the multiple mapping types index for migration.

In this chapter, we are going to learn about mapping APIs. In Elasticsearch, mapping is a data model that describes the structure of a document. It allows you to specify fields, field types, relationships between documents, data conversion rules, and so on. Schema-less only means that documents can be indexed without specifying the schema in advance, because the schema is dynamically derived from the first document index structure based on the built-in mapping rules in Elasticsearch. If you have a good search database design plan, you should use explicit...

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